Alternatives and similar repositories for LoRAPrune

Users that are interested in LoRAPrune are comparing it to the libraries listed below

• ROIM1998 / APT
  [ICML'24 Oral] APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference
  ☆43Updated last year
• zyxxmu / DSnoT
  Official Pytorch Implementation of Our Paper Accepted at ICLR 2024-- Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLM…
  ☆49Updated last year
• ycjing / Awesome-Model-Merging
  A curated list of Model Merging methods.
  ☆92Updated 10 months ago
• htqin / IR-QLoRA
  [ICML 2024 Oral] This project is the official implementation of our Accurate LoRA-Finetuning Quantization of LLMs via Information Retenti…
  ☆65Updated last year
• osehmathias / lisa
  LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning
  ☆31Updated last year
• UNITES-Lab / MC-SMoE
  [ICLR 2024 Spotlight] Code for the paper "Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy"
  ☆86Updated 3 weeks ago
• yxli2123 / LoSparse
  ☆58Updated last year
• locuslab / massive-activations
  Code accompanying the paper "Massive Activations in Large Language Models"
  ☆169Updated last year
• SempraETY / Pruning-via-Merging
  ☆18Updated 7 months ago
• TsinghuaC3I / SoRA
  [EMNLP 2023, Main Conference] Sparse Low-rank Adaptation of Pre-trained Language Models
  ☆79Updated last year
• mrflogs / LoRA-Pro
  Official code for our paper, "LoRA-Pro: Are Low-Rank Adapters Properly Optimized? "
  ☆126Updated 3 months ago
• CASIA-IVA-Lab / FLAP
  [AAAI 2024] Fluctuation-based Adaptive Structured Pruning for Large Language Models
  ☆56Updated last year
• BaiTheBest / SparseLLM
  Official Repo for SparseLLM: Global Pruning of LLMs (NeurIPS 2024)
  ☆64Updated 3 months ago
• pixeli99 / OWS
  Official Pytorch Implementation of "Outlier-weighed Layerwise Sampling for LLM Fine-tuning" by Pengxiang Li, Lu Yin, Xiaowei Gao, Shiwei …
  ☆33Updated last month
• liyunqianggyn / Awesome-LLMs-Pruning
  Awesome LLM pruning papers all-in-one repository with integrating all useful resources and insights.
  ☆96Updated 7 months ago
• Lucky-Lance / Expert_Sparsity
  [ACL 2024] Not All Experts are Equal: Efficient Expert Pruning and Skipping for Mixture-of-Experts Large Language Models
  ☆94Updated last year
• LINs-lab / DynMoE
  [ICLR 2025] Dynamic Mixture of Experts: An Auto-Tuning Approach for Efficient Transformer Models
  ☆116Updated last week
• nbasyl / DoRA
  Official implementation of "DoRA: Weight-Decomposed Low-Rank Adaptation"
  ☆124Updated last year
• MohammadrezaBanaei / LoRA-XS
  LoRA-XS: Low-Rank Adaptation with Extremely Small Number of Parameters
  ☆35Updated 4 months ago
• lliai / Awesome-LoRA-Low-Rank-Adaptation
  Awesome-Low-Rank-Adaptation
  ☆110Updated 9 months ago
• hahnyuan / ASVD4LLM
  Activation-aware Singular Value Decomposition for Compressing Large Language Models
  ☆74Updated 8 months ago
• DavidFanzz / SCMoE
  ☆26Updated last year
• horseee / dKV-Cache
  ☆88Updated last month
• sdc17 / UPop
  [ICML 2023] UPop: Unified and Progressive Pruning for Compressing Vision-Language Transformers.
  ☆103Updated 6 months ago
• Chongjie-Si / Subspace-Tuning
  A generalized framework for subspace tuning methods in parameter efficient fine-tuning.
  ☆147Updated 3 weeks ago
• yangyifei729 / LaCo
  Official implementation for LaCo (EMNLP 2024 Findings)
  ☆17Updated 9 months ago
• Lucky-Lance / SPP
  [ICML 2024] SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models
  ☆21Updated last year
• CASE-Lab-UMD / Unified-MoE-Compression
  The official implementation of the paper "Towards Efficient Mixture of Experts: A Holistic Study of Compression Techniques (TMLR)".
  ☆71Updated 3 months ago
• harveyhuang18 / EMR_Merging
  [NeurIPS 2024 Spotlight] EMR-Merging: Tuning-Free High-Performance Model Merging
  ☆59Updated 4 months ago
• TianjinYellow / EdgeDeviceLLMCompetition-Starting-Kit
  ☆43Updated 8 months ago